Lots of people engrossed within the AI-and-jobs debate maintain asking the identical query: what number of jobs will disappear. Manish Sabharwal, co-founder of TeamLease Services and a veteran voice on India’s labor economics, thinks that’s the unsuitable start line.
The query that truly issues for India, he argues, is how the nation manages the productiveness AI unlocks, and who finally ends up higher off due to it.
Job counts transfer up and down each quarter for a big selection of causes and never simply AI. However the query of how AI led productiveness beneficial properties shall be distributed between capital and labour stays persistent and it’s the one this piece is constructed round.
Headline numbers provide solely half the image
Monitoring headline IT numbers reveals simply how non-linear this transition shall be. Trade knowledge from tech staffing specialist Xpheno confirmed that IT more energizing hiring had declined roughly 80% industry-wide from FY22 to FY25.
Nonetheless, latest Q1 FY27 outcomes from Indian IT majors have sophisticated the image with some IT majors equivalent to TCS making a considerable addition to their workforce, revealing a deeply fragmented company technique somewhat than a straight-line decline.
| Firm | Q1 FY27 Internet Headcount Change | Strategic Takeaway |
| TCS | +9,279 staff | Onboarded 14,000 freshers in its strongest quarterly headcount addition in practically 4 years; CEO Okay Krithivasan pushed again on fears that AI will shrink the workforce. |
| HCLTech | -3,292 staff | The steepest sequential drop in two years; income per worker rose 3.3% YoY as automation and AI infusion allowed them to ship work with fewer folks. |
This divergence reveals that greater productiveness and employment progress should not have a easy linear relationship. The story of AI reshaping the Indian job market is one which comes full of a number of caveats, considerations and guarantees.
As we start to untangle the identical, it turns into vital for us to take a look at earlier know-how primarily based job market disruptions to find out how folks have historically reacted to such change.
What historical past tells us about know-how shocks
“Each technological wave thus far has created extra nervousness than unemployment, as a result of we’re higher at predicting which jobs shall be affected than predicting which jobs shall be created,” Sabharwal says.
He’s watched this play out earlier than through the automation of producing, by means of the 2008 monetary disaster, by means of the hiring freeze that got here with Covid and the digitisation led overhiring spree that got here after.
“The distinction this time is that AI touches cognitive work somewhat than bodily work, so the educated really feel personally and significantly susceptible. However historical past suggests know-how destroys sure duties a lot quicker than it destroys complete occupations.”
This distinction is vital. Jobs will not be single actions. They’re bundles of routine and non-routine duties. Expertise can take away some parts of a job with out eliminating the occupation itself.
An earlier Financial Express analysis of Anthropic’s Financial Index discovered that routine work connected to junior roles equivalent to primary buyer assist, analysis, IT assist and documentation have been essentially the most uncovered to automation. In consequence, junior roles at massive company roles have been being extra closely re-designed than senior ones.
The proof pointed much less in the direction of the in a single day disappearance of whole professions and extra in the direction of a redistribution of duties between employees and AI programs.
Not unemployment: Probably the most worrying AI-linked Indian job market downside
Sabharwal locations the AI debate inside a a lot older weak spot in India’s financial system. “India’s downside just isn’t unemployment, it has been 4-8% since 1947 however employer poverty,” he mentioned.
“Most Indians work, however too many work in enterprises which can be too small, too casual and have very low productiveness to supply steadily rising wages, structured studying or significant profession mobility. AI by itself doesn’t essentially change this prognosis. If something, it reinforces it,” he defined.
As per knowledge posted by the Ministry of Statistics and Programme Implementation (MoSPI), India hosted an estimated 7.92 crore non-agricultural institutions using 12.81 crore employees in 2025.
These embody small producers, retailers, restore retailers, eating places, transport operators and different companies that type the on a regular basis base of India’s casual financial system. Whereas these microbusiness companies are very important for quick livelihoods, their sub-scale nature retains wages low and profession development minimal.
Find out how to resolve employer poverty ?
If employer poverty is the underlying weak spot, knowledge means that greater productiveness can possible be a part of the remedy. At its easiest, productiveness means producing extra worth with the identical quantity of labour, capital and time.
“International locations grow to be affluent not as a result of they shield present jobs however as a result of they repeatedly create higher-productivity work. AI is one other productiveness know-how,” Sabharwal instructed Monetary Categorical. Traditionally, greater productiveness applied sciences have lowered prices, expanded markets and created occupations that didn’t beforehand exist.
Although primary digital entry has improved with the share of unincorporated enterprises utilising the web for enterprise functions rising to 40%, the Financial Survey of India signifies that wider productiveness and job creation beneficial properties stay unrealised.
Low-cost AI instruments might help small retailers generate product descriptions, translate buyer messages, reply routine queries, and make use of modest social media advertising capabilities to achieve consumers past their neighbourhood.
Nonetheless it turns into vital for us to notice right here that entry to a chatbot doesn’t routinely translate into organisational adoption.
As micro companies nonetheless require dependable connectivity, usable knowledge, working capital, digitally succesful staff and managers keen to alter established processes to efficiently unlock AI led financial progress. With out these foundations, AI could stay a handy instrument somewhat than grow to be a real productiveness engine.
Analysis by the OECD and the Competition Commission of India on the advantages and challenges of adoption of AI in work factors in the identical path. As per researchers behind these institutes, this structural divide units up two wildly completely different financial paths for the nation:
The Inclusive Path: Within the extra inclusive state of affairs, entry to AI, finance and related coaching permits smaller casual and mid-sized companies to enhance productiveness, attain wider markets and develop into succesful employers.
The Focus Path: Within the various state of affairs, the beneficial properties stay concentrated amongst massive firms with the capital, knowledge and managerial capability to reorganise whole companies round AI. These corporations could broaden output and market share significantly with out producing a proportionate enhance in employment.
India’s productiveness problem is due to this fact not solely about making particular person employees quicker. It’s about creating extra employers able to changing know-how into scale.
Have to strike the precise stability between productiveness and jobs
AI might help firms produce extra with the identical workforce or preserve output with fewer folks. Whether or not India beneficial properties higher jobs or just leaner payrolls will depend upon how companies use that productiveness dividend.
Researchers on the World Financial Discussion board have forecasted for 92 million jobs to be eradicated due to AI by 2030 and 170 million can to be created which leaves a web acquire of 78 million.
However the employment beneficial properties don’t come routinely or painlessly. As per analysis carried out by World Financial Discussion board companies should actively experiment and rebuild workflows to unlock significant beneficial properties. This may be greatest understood by means of the next instance.
When an engineer writes code quicker or an analyst processes knowledge quickly, a agency beneficial properties surplus productive capability that it could deploy in one in every of two methods:
Market Enlargement (Case 1): Corporations can leverage their boosted productiveness to deal with progress by coming into new markets, launching new merchandise, bettering their service high quality and creating extra strategic new jobs within the course of as AI takes over routine work.
Payroll Pruning (Case 2): Corporations select to keep up the very same output as earlier than, however with considerably fewer folks, focusing merely on value discount.
Whereas organisation productiveness rises in each instances, the impact on employment stays fully completely different. For this reason researchers behind the financial survey of India have argued that the query of synthetic intelligence’s affect on work can’t be lowered as to whether AI improves effectivity. It clearly can. The extra vital query is the place the beneficial properties from that effectivity go.
It’s the scale and methodology at which enterprises select to go ahead with both one of many pathways that can form how AI impacts India’s labour market.
What does {industry} knowledge recommend?
Early company knowledge means that productiveness and employment progress should not have to maneuver in reverse instructions. PwC’s 2026 International AI Jobs Barometer discovered firms in extremely AI-exposed sectors recorded a 34% rise in workforce productiveness between 2018 and 2025 (versus 24% within the least-exposed sectors), alongside greater headcount progress.
The outcomes don’t imply AI will routinely produce extra jobs. They point out that firms able to changing new know-how into further merchandise and income can increase productiveness with out essentially shrinking employment.
Nonetheless, it turns into vital to notice right here that this twin productiveness stays extremely tough to achieve. In PwC’s international survey of 4,454 CEOs throughout industries, solely 12% reported reaching each greater headcount and better income from AI funding in 2025. The opposite 88% noticed both greater income with greater prices, or value cuts with marginal income affect.
As per PwC researchers, the stark hole highlights that giving staff AI instruments just isn’t the identical as redesigning a enterprise round them — although 56% of these CEOs nonetheless count on the structural funding to repay over an extended horizon.
The takeaway from analysis carried out by the World Financial Discussion board and PwC is evident: re-designing enterprise workflows to enrich AI capabilities takes time and experimentation. Moreover, in a whole lot of instances these transitions could not instantly translate into productiveness and financial beneficial properties.
Workforce planning is shifting from ladders to portfolios
Whereas now we have previously talked about how AI has substantially raised the employability bar for fresher roles, now requiring proof of labor (internships, tasks) alongside AI literacy and human abilities equivalent to stakeholder administration and determination making.
Right here we deal with AI’s affect on workforce planning and organisational design as an entire.
Employment started shifting from being a lifetime contract to a taxi cab relationship a very long time in the past. AI has accelerated that pattern however didn’t begin it,” Sabharwal instructed Monetary Categorical.
For many years, extra clients typically required extra staff, extra layers of supervision and bigger assist features. AI weakens that connection between financial progress and worker headcount.
A smaller staff can now draw upon automated analysis, coding, buyer assist and administrative capability to assist a rising buyer base.
Staffing businesses count on firms to quickly organise themselves round a smaller everlasting core, supported by fixed-term staff, consultants, apprentices, freelancers, challenge employees and AI programs.
TeamLease’s personal knowledge reveals a rise in firms’ urge for food for contract employees.”Each employer balances three dangers — enterprise uncertainty, technological uncertainty and regulatory uncertainty. Versatile staffing helps handle all three,” the co-founder of teamlease instructed Monetary Categorical.
His broader declare is that the ladder metaphor for careers now not matches.
“Careers have gotten portfolios somewhat than ladders. Employees will more and more transfer between everlasting employment, fixed-term work, consulting, challenge work, apprenticeships, freelancing and entrepreneurship over their working lives.”
As per Sabharwal the vital query to look presently isn’t just the rise in contract work compared to everlasting postings however to know whether or not employees proceed to amass abilities and stay employable.
“Employability is the one actual job safety,” he instructed Monetary Categorical.
The truth of this shift is already seen in LinkedIn’s Work Change Report, which notes that professionals coming into the workforce immediately are on tempo to carry twice as many roles over their careers in comparison with a era in the past.
How ought to India take a look at making ready its workforce for an AI led Trade
For policymakers and educators, the quick problem is guaranteeing that India’s large youth demographic strikes with the know-how somewhat than being left behind by it.
Sabharwal argues that India’s present instructional mannequin requires a structural re-design.
“For many years, we’ve operated on the belief that schooling comes first and work comes later. That made sense when information modified slowly. In the present day, information is depreciating a lot quicker than levels. AI has shortened the half-life of technical abilities.”
The answer in his view just isn’t merely including an AI topic to the curriculum, however structurally integrating studying with energetic work.
Sabahwal additionally pointed to schooling fashions of nations with low employment charges equivalent to Germany, Switzerland, and Austria for instance of what India can look to alter in India’s schooling system.
Germany, Switzerland and Austria maintain nicely established apprenticeship primarily based studying fashions that interlock school rooms with workplaces the place college students get to contribute to the actions within the trendy office a lot sooner than in India.
Sabharwal argues that graduates in these settings don’t grow to be employable as a result of they’ve spent 4 years in school rooms. They grow to be employable as a result of they’ve repeatedly solved actual issues with colleagues and clients which additionally helped them choose up tender abilities which can be turning into more and more beneficial immediately.
The advantages of Sabharwal’s resolution for the campus to company pipeline will not be theoretical and have been backed by the most recent Financial survey of India.
The newest financial survey that got here out earlier than the finances this 12 months estimated that broader labour reforms, paired with vocational coaching and higher employee mobility might add 1.25 share factors to GDP by 2030. Providing an official, numeric model of Sabharwal’s personal prescription of apprenticeships, mobility and steady skilling.
Sabharwal has spent greater than twenty years constructing TeamLease into one in every of India’s largest staffing and workforce-solutions corporations. Alongside his distinguished company profession, he has beforehand additionally served on RBI’s Central Board and a number of other authorities committees on abilities, schooling and employment.
What job seekers ought to do to enhance employability ?
Requested for one takeaway for readers navigating an AI-led, hypercompetitive job market, Sabharwal provided a single concept: don’t optimise your profession round immediately’s instruments; optimise it round tomorrow’s adaptability.
Each main technological revolution has eradicated some duties, modified many others and created completely new occupations that no person might predict beforehand. AI shall be no completely different.
As per Sabharwal, the graduates who thrive gained’t essentially be the very best coders or the very best immediate engineers. They’ll be the individuals who mix technical fluency with enduring human capabilities like curiosity, judgment, innovation and skill to be taught repeatedly.
He distills this private structure into three foundational concepts for children to observe: fitrat (understanding one’s instincts), riyaaz (sustained effort), and taalim (steady studying).
Translating this right into a profession path requires a shift in how professionals consider alternatives. Sabharwal recommends candidates coming into the job market immediately to prioritise progress over legacy labels.
As per the Teamlease founder, younger graduates coming into the market immediately shouldn’t resolve their first job utilizing conventional filters like manufacturing versus providers or beginning wage as a substitute they need to attempt to work for high-growth firms with dynamic managers the place they’ll take up vital tender abilities.
“Typically I believe an enormous job in a small firm is best studying than a small job in an enormous firm,” Sabharwal instructed Monetary Categorical whereas emphasising on the significance of early profession publicity to capabilities like determination making and management.
The takeaway from Sabharwal’s insights and WEF knowledge was clear: As instruments and applied sciences get reinvented each few years, the very best long run profession technique stays the one centered on constructing character, judgment, and studying agility which compound for many years.
The coverage problem
For India, defending each present activity just isn’t a sustainable employment technique. Neither is assuming that markets will routinely create higher work for each individual displaced.
The coverage problem is to speed up the creation of higher-productivity employers whereas serving to employees transfer with know-how. Sabharwal locations higher schooling, apprenticeships, labour mobility and steady studying on the centre of this transition.
AI will nearly definitely enable India to supply extra with much less time and fewer routine inputs. Whether or not that turns into an answer to the productiveness downside or an aggravation of the roles downside depends upon what occurs subsequent.